Linking Health Indicators to Refinery Emissions
Niklas Lollo
Filters
This analysis looks at
Correlations
Plots1
t-tests for Statistical Significance2
These tests compare the difference between the population mean health outcome (e.g. heart rate) and the mean health outcome when the environmental input (e.g. methane) is above its median value. Actually does not do this anymore.
- To do: should make this analysis (maybe also) look at when pollutant is above permitted limit or if it is present at all.
Spatial Analysis
Plot points
## OGR data source with driver: ESRI Shapefile
## Source: "../refinery_data/location/BaseMapGrid", layer: "GRD_PWD_BaseMap_0106"
## with 446 features
## It has 11 fields
Autocorrelation
## [1] "Moran's I p-value: 0.84"## [1] "Moran's I z-score: -0.207555698373681"Load Cal Enviro Screen
## OGR data source with driver: ESRI Shapefile
## Source: "../refinery_data/location/CES3Results", layer: "CES3Results"
## with 8035 features
## It has 63 fields
## Integer64 fields read as strings: Population ZIP CIscoreP Ozone_Pctl PM_2_5_Pct DPM_pctl DW_pctl Pest_pctl TR_pctl Traff_Pctl Clean_Pctl GW_pctl Haz_pctl Imp__Water IWB_pctl Solid_pctl Poll_pctl Asthma_Pct LBW_pctl CVD_pctl Edu_pctl Ling_pctl Pov_pctl Unem_pctl HB_pctl Pop_Pctl## An object of class "SpatialPolygonsDataFrame"
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## Tract_1 Percentile Population County ZIP City CIscore
## 4373 6013303203 46-50% 8491 Contra Costa 94513 Brentwood 23.56
## 4374 6013302009 41-45% 5641 Contra Costa 94531 Antioch 21.17
## 4375 6013302010 36-40% 10039 Contra Costa 94561 Oakley 19.49
## 4376 6013313204 61-65% 5542 Contra Costa 94521 Concord 31.30
## 4377 6013313203 41-45% 3222 Contra Costa 94565 Pittsburg 22.29
## 4378 6013302005 76-80% 6592 Contra Costa 94561 Oakley 39.94
## CIscoreP Ozone Ozone_Pctl PM2_5 PM_2_5_Pct Diesel_PM DPM_pctl
## 4373 47 0.042 32 7.86 18 21.60 66
## 4374 41 0.042 32 7.86 18 27.16 80
## 4375 37 0.042 32 7.86 18 24.93 76
## 4376 62 0.038 22 7.86 18 9.35 27
## 4377 44 0.038 22 7.86 18 11.03 31
## 4378 76 0.042 32 7.86 18 21.12 65
## DrinkingWa DW_pctl Pesticides Pest_pctl Tox_Releas TR_pctl Traffic
## 4373 423.91 44 29.346 68 227.22 39 602.44
## 4374 98.57 8 15.486 62 216.45 38 442.11
## 4375 189.22 14 9.656 58 183.22 34 324.31
## 4376 148.37 9 0.000 0 934.70 59 406.40
## 4377 230.99 23 0.000 0 1424.19 64 888.68
## 4378 189.25 14 42.710 70 182.85 34 580.41
## Traff_Pctl Cleanups Clean_Pctl Groundwate GW_pctl Haz_Waste Haz_pctl
## 4373 42 6.50 50 10.00 50 0.05 26
## 4374 25 0.75 11 0.00 0 0.10 43
## 4375 14 2.15 28 3.00 22 0.02 16
## 4376 22 14.00 75 34.75 85 0.00 0
## 4377 62 0.00 0 0.00 0 0.10 43
## 4378 39 3.10 33 27.00 79 2.66 94
## Imp__Water IWB_pctl Solid_Wast Solid_pctl PollutionS Poll_pctl Asthma
## 4373 10 86 0 0 5.34 54 66.65
## 4374 0 0 0 0 3.53 17 108.34
## 4375 8 76 0 0 4.06 27 90.16
## 4376 4 49 7 83 4.24 30 115.41
## 4377 0 0 7 83 3.62 18 150.18
## 4378 8 76 0 0 5.52 58 92.07
## Asthma_Pct Low_Birth_ LBW_pctl Cardiovasc CVD_pctl Education Edu_pctl
## 4373 76 4.51 39 13.23 94 2.3 7
## 4374 94 4.01 26 11.40 85 9.5 37
## 4375 89 4.35 35 13.03 93 8.7 35
## 4376 96 5.91 75 11.51 86 21.3 64
## 4377 99 3.19 12 14.45 97 16.1 55
## 4378 90 5.37 63 13.27 94 13.8 49
## Linguistic Ling_pctl Poverty Pov_pctl Unemployme Unem_pctl Housing_Bu
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## 4374 4.0 30 35.4 53 8.2 41 24.1
## 4375 1.0 6 11.0 9 5.5 17 15.1
## 4376 9.1 56 31.5 47 11.8 69 17.7
## 4377 6.5 44 28.1 42 8.4 42 21.6
## 4378 3.2 24 42.7 64 11.9 69 26.3
## HB_pctl PopCharSco Pop_Pctl Children__ Pop_11_64_ Elderly___
## 4373 49 4.41 38 15.5 70.8 13.7
## 4374 74 6.00 62 17.0 77.9 5.1
## 4375 36 4.81 45 14.6 78.8 6.6
## 4376 49 7.38 81 15.1 75.6 9.3
## 4377 66 6.16 64 13.4 79.1 7.5
## 4378 80 7.24 80 15.6 74.5 9.9
## Hispanic__ White____ African_Am Native_Ame Asian_Amer Other____
## 4373 21.2 55.6 8.3 0.4 10 4.5
## 4374 25.8 25.7 24.3 0.4 17.4 6.4
## 4375 28.3 56.4 4.7 0.3 6.2 4
## 4376 45 28.2 12.5 0.3 10.7 3.4
## 4377 39.7 28.1 8.8 0.4 18.4 4.7
## 4378 39.1 46.2 6.8 0.8 3.4 3.7
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